NR 505 Discussion Elements of Quantitative Research: Design and Sampling
NR 505 Discussion Elements of Quantitative Research: Design and Sampling
NR 505 Discussion Elements of Quantitative Research: Design and Sampling
The single quantitative research study article that I have chosen is an article that discusses; does aerobic exercise reduce postpartum depressive symptoms? Throughout this article it looks at the population of mothers that are one year or less postpartum and women with depressive symptoms that are measured by a questionnaire or diagnostic tool (Pritchett, Daley, & Jolly, 2017). This particular research study I would have to say is non experimental because there is intervention but one does not have control over whether or not these postpartum mothers exercise and how much they exercise, they have to go by what they say they do and the intensity of their exercise.
Intervention is that there were different trial groups which included; group exercise interventions, exercise counseling was provided and the participant was allowed to choose their own form of exercise (Pritchett, Daley, & Jolly, 2017). They were aiming to achieve approximately 30 minutes of moderate exercise three to five times weekly. The observation/data collected during this was to see if exercise had an effect on decreasing depressive symptoms in postpartum women. The study did find that overall exercise is an effective treatment for postpartum depression. The random assignments were of women whom chose their own exercise that they did, women that were assigned to groups for exercise, and other women that received exercise counseling (Pritchett, Daley, & Jolly, 2017).
When looking at probability vs non-probability for this article I would have to go with non-probability for this because this just focuses on postpartum women, so not all postpartum women if they are one year of having a baby would not qualify for this study. Non-probability is when not every member of the population has the same chance of being included in the study. This study focuses on women whom are one year or less postpartum.
An advantage to using non-probability is the population being studied is narrowed down to just mothers whom are one year postpartum. A disadvantage to this is that postpartum depression can last past one year of childbirth in some women. So these women are being excluded from the study.
A random assignment was used for this study as women were either in a group, had counseling, or chose the exercise that they wanted to do. This can strengthen the study as it narrows down what area was most effective whether it be exercise in a group setting, individualized, or the counseling about exercise.
Pritchett, R. V., Daley, A. J., & Jolly, K. (2017). Does aerobic exercise reduce postpartum depressive symptoms? British Journal of General Practice, 67. https://doi.org/10.3399/bjgp17x692525 (Links to an external site.)Links to an external site.
Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS NR 505 Discussion Elements of Quantitative Research: Design and Sampling:
I chose a qualitative research study that looked at primary care physicians and how they screen for military service and post-traumatic stress disorder (PTSD). This study is pertinent to my PICo question, are post war veterans at a higher risk for suicide as they re-integrate into society? As a future nurse practitioner (NP), I see a correlation with health care providers understanding if their patients have served in the military and if they may be experiencing physical or mental symptoms that are adversely affecting their well-being as a way of reducing suicide risk among veterans. Mohler & Sankey-Deemer (2017), discuss the link between PTSD and veteran suicide and how veteran suicide has been on the rise in the last ten years. Due to challenges with distance and access to a veteran health facility, Mohler (2017), discusses the importance of primary care physicians screening the patients for military service and any health concerns they may be experiencing as a result of time served.
Research study design: Non- Experimental
This study falls within the parameters of non-experimental because an intervention is not introduced, and the researchers are simply collecting data from primary care physicians. Polit & Beck (2017), discuss the researcher role in non-experimental study as simply being bystanders without introducing any treatments that could affect the data.
Representation for the research study: O
Type of sampling: Nonprobability
My rationale for choosing this sample style was simply by the wording of the sample description within the article. According to Mohler (2017), primary care physicians were located using online search engines, Facebook, provider directories, and professional directories and a comprehensive list of all primary care physicians within the chosen demographic area was not done. Rural primary care physicians were likely to have been excluded due to likelihood of being active and present on modern internet websites and search engines. Polit (2017), describes nonprobability as a sampling method in which every element does not have a chance to be included. An advantage to this sample method would be the ease in locating primary care physicians to participate and have a large sample of participants with which to work with. The disadvantage would be the likely hood of excluding rural primary care physicians when research has shown veterans in rural communities have a higher risk of suicide.
Random assignment: No random assignment was utilized.
According to Polit (2017), random assignment is used when assigning participants to treatment conditions or interventions. Because this was a non-experimental research design, no interventions were utilized and therefore no random assignment applied.
Mohler, K. M., & Sankey-Deemer, C. (2017). Primary Care Providers and Screening for Military Service and PTSD. AJN American Journal of Nursing, 117(11), 22.
Polit, D. & Beck, C. (2017). Essentials of nursing research: Appraising evidence for nursing practice (9th ed.). Philadelphia, PA: Wolters Kluwer.
This week I chose the following question for my professor response: Can you determine all members of your population of interest? Polit & Beck (2017), discuss the population of interest as all individuals within the group of interest. The interesting aspect of this question is initially I would have quickly responded with a yes and provided information to rationalize my decision however, research on my evidenced based practice project has shown me my topic of interest has a far more reaching population than I had previously understood.
As I research post war veterans and their risk for suicide, I am more keenly aware of the varying population of veteran service members. For example, women serving in the military could have different post war concerns and very little research has been conducted to determine interventions specific to their needs. Chapman &Wu (2104), discuss the lack of research among female veterans despite their increase in mental health needs and exposure to trauma. Ethnicity and minority status could also be populations of interest under the general umbrella of post war veterans. Nock et.al (2018), discuss the military career variable as a population of interest and determining whether or non-commissioned officers are more likely to commit suicide as opposed to those who are commissioned officers. Other populations of interest within the post war veteran status are those with a mental health diagnosis or a new physical handicap. Age and demographical area would also need to be considered as statistics show younger veterans in rural communities have a higher risk for suicide. Male and female veterans ages 18-34 have a higher rate of suicide than individuals who are older (Chapman, 2014). These varying components of the post war veteran could significantly change the overall data if individuals are chosen simply based on their recent service.
To answer the question, I do believe you can determine all members of your population of interest for research. In my opinion, the research data will be altered based on how broad or narrow the researcher makes their population. For my research, I can make the population broad by utilizing men and women veterans returning from deployment or I can narrow the population by limiting the variables to non-commissioned officers, specific age ranges or demographics. Continued research allows us to pinpoint specific areas of need within a general population of interest and determine more appropriate interventions.
Chapman, S. C., & Wu, L. (2014). Review: Suicide and substance use among female veterans: A need for research. Drug and Alcohol Dependence, 1361-0.doi:10.1016/j.drugalcdep.2013.11.009
Nock, M. K., Millner, A. J., Joiner, T. E., Gutierrez, P. M., Han, G., Hwang, I., & Stein, M. B. (2018). Risk Factors for the Transition from Suicide Ideation to Suicide Attempt: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Journal of Abnormal Psychology, 127(2), 139-149.
Polit, D. & Beck, C. (2017). Essentials of nursing research: Appraising evidence for nursing practice (9th ed.). Philadelphia, PA: Wolters Kluwer.
I found your post quite informative. I appreciate you interest in veterans risk to suicide. As with many mental health areas, I feel this one that is a taboo subject. I have met individuals with PTSD and it is a sad thing to witness. It makes sense that someone going through PTSD may be at risk for committing suicide however I never really consider the amount of risk this could pose while reintegrating in to society. I find great value in the study you discussed. You mention that suicide in veterans has been on the rise over the last ten years. I am curious to know if there has been any research to determine why this is occurring. While this stud may not have provided an intervention, I still find it useful as it is important to determine how primary care providers are screening for this. I have heard numerous stories about veterans living on the streets, not being able to make it financially, or not receiving adequate healthcare. It seems that the veteran hospitals just lack the resources to keep up with the demands. As a society I feel we can do better for those who served for our country. Thank you for sharing your thoughts.
The research study design that was chosen was one that relates to my profession as a Family Nurse Practitioner, who plans to work in a rural area. The study analyzed small, rural emergency facilities that treated patients that live in rural populations. The method included Pubmed/Medline and Embase databases that were systemically reviewed between 1980 and the present (Baker & Dawson, 2013). The research design is experimental. The design included a disposition record that measured the admission rates, ages of patients seeking emergent care, and number of unplanned healthcare rendered from small, rural facilities.
Small rural emergency departments are under-researched, despite being common and controversial (Baker & Dawson, 2013). The appropriate representation for this research article was used, which is observation (O) and data collection. A systemic review of observational studies were performed to determine what is known about the patients that the small, rural facilities treated. This included the interventions that were given and how effective the interventions were in treating the patients (Baker & Dawson, 2013).
The type of sampling that was used was probability. Studies were selected as a representative sample if they described hospital-affiliated emergency care facilities which were open twenty-four hours every day (Baker & Dawson, 2013). The facilities had to be rural and non-urban in order to be included in the study. Studies were excluded if facilities saw more than 15,000 patients yearly (Baker & Dawson, 2013).
The advantage of the probability sampling is that this type of sampling is highly representative of the population that is being studied. This will lead to a more accurate conclusion. One disadvantage of this type of sampling is the increase time that it may take to gather and process data, due to the large sample groups.
There were random assignments to this research study article. The study used quantitative data which demonstrated activity and performance of the staff and patients (Baker & Dawson, 2013). The group included studies of patients that sustained injuries, poisoning, and illnesses that required medical attention with 15 minutes of arrival to the emergency department (Baker & Dawson, 2013). The random assignments that were reviewed in this article strengthen the research study design by permitting studies that determined the quantity of literature regarding how small, rural emergency departments treat patients who seek emergent, unplanned healthcare. The research article allowed a hypothesis to be concluded that can identify a small number of common characteristics that can be used as a basis for future research in this area (Baker & Dawson, 2013).
Reference
Baker, T., & Dawson, S.L. (2013). What Small Rural Emergency Departments do: A Systemic Review of Observational Studies. The Australian Journal Of Rural Health, 21(5), 254-261. doi:10.111/ajr.12046
As mentioned in previous discussion posts, I am embarking on the family nurse practitioner track. I am interested in expanding on my current nursing skills and being able to provide for my patients on a more autonomous level. My passion is to help patients manage their chronic conditions while utilizing patient centered care. I am a firm believer in that model. There are certain things that are important to me when developing a plan of care. It is important for healthcare providers to have open communication with their patients. This ensures the patient’s needs are met.
Bin Chen and colleagues conducted a study that examined the role of diabetic education in the improvement of depression in newly diagnosed type two diabetics. According to Chen and colleagues ( 2013) method of data collection included assessing depression and diabetes specific emotional distress in participants before and after a two week diabetes education conducted by a nurse (p. 1148). According to our weekly lesson, quasiexperimental designs include an intervention however does not include random assignment of participants into groups (CCN, 2018). Based on this, I have determined the above study is a quasiexperimental design as the researchers did not randomly assign participants in to groups yet included an intervention.
An appropriate representation for the above study includes:
| Quasiexperimental Design: pretest-post test | Experimental Group | O1 | X | O2 |
The sample for the above study included twelve hundred adult males that were newly diagnosed with type two diabetes (Chen et al, 2013, p. 1148). Researchers excluded individuals with acute complications of diabetes, cardiovascular disease, cerebra-vascular disease, symptomatic peripheral arteries disease, or other chronic somatic disease (Chen et al, 2013, p. 1148). In addition, Chen and colleagues (2013) ensured none of the participants had hyperglycemia nor had they been assessed or diagnosed with depression prior to the study (p.1148). Our weekly lesson discusses, a nonprobability sample does not include every member of the population and does not include randomly assigning participants to groups (CCN, 2018). This study includes a nonprobability sample. The sample for this study included adult males from Northeast China (Chen et al, 2013, p. 1148). The researchers were looking for specific participants to participate in the study and did not include randomly assigning the participants in to groups. While it can be impossible to include every member of the target population in the study, a nonprobability sample can create bias. Despite the bias that can be created, an advantage of utilizing a nonprobability sample is that you are still able to support your evidence based practice project. As with most things, sometimes the benefits outweigh the risks.
References:
Bin, C., Xiyao, Z., Xiuping, X., Xiaofeng, L., Lu, Y., Xu, H., & … Can, C. (2013). Diabetes education improves depressive state in newly diagnosed patients with Type 2 diabetes. Pakistan Journal of Medical Sciences, 29(5), 1147-1152.b doi:10.12669/pjms.295.3573 permalink: https://chamberlainuniversity.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=94136883&site=eds-live&scope=site (Links to an external site.)Links to an external site.
Chamberlain College of Nursing. (2018). Week three lesson: Developing new evidence: Quantitative research studies. Retrieved from: https://chamberlain.instructure.com/courses/27019/pages/week-3-lesson?module_item_id=3114402